ArticleAging2024
Identification of a fatty acid metabolism-related gene signature to predict prognosis in stomach adenocarcinoma.
Article in Aging, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
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Who cites it
3 citing papers in PubMed.
- ORMDL2 Promotes the Growth of Glioma through mTORC1-Mediated Fatty Acid Metabolism.Applied biochemistry and biotechnology · 2025Article
- Alternative Splicing in Tumorigenesis and Cancer Therapy.Biomolecules · 2025Review
- A Prognostic Riskscore Model Related toInternational journal of genomics · 2025Article
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Authors and funding
9 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundFatty acid metabolism (FAM) contributes to tumorigenesis and tumor development, but the role of FAM in the progression of stomach adenocarcinoma (STAD) has not been comprehensively clarified.
methodsThe expression data and clinical follow-up information were obtained from The Cancer Genome Atlas (TCGA). FAM pathway was analyzed by gene set enrichment analysis (GSEA) and single-sample GSEA (ssGSEA) methods. Univariate Cox regression analysis was conducted to select prognosis genes. Molecular subtypes were classified by consensus clustering analysis. Furthermore, least absolute shrinkage and selection operator (Lasso) analysis was employed to develop a risk model. ESTIMATE and tumour immune dysfunction and exclusion (TIDE) algorithm were used to assess immunity. pRRophetic package was conducted to predict drug sensitivity.
resultsBased on 14 FAM related prognosis genes (FAMRG), 2 clusters were determined. Patients in C2 showed a worse overall survival (OS). Furthermore, a 7-FAMRG risk model was established as an independent predictor for STAD, with a higher riskscore indicating an unfavorable OS. High riskscore patients had higher TIDE score and these patients were more sensitive to anticancer drugs such as Bortezomib, Dasatinib and Pazopanib. A nomogram based on riskscore was an effective prediction tool applicable to clinical settings. The results from pan-cancer analysis supported a prominent application value of riskscore model in other cancer types.
conclusionThe FAMRGs model established in this study could help predict STAD prognosis and offer new directions for future studies on dysfunctional FAM-induced damage and anti-tumor drugs in STAD disease.
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